000			01851nam a22001457a 4500
999			_c528714 _d528714
008			250106b ||||| |||| 00| 0 eng d
100			_aAbdul-Rahaman, A.R. Martha, C. and Ayamba, E.C. _949714
245			_aExchange rate models and the management of forex losses in Ghana: Modelling exchange rate volatilities for businesses
260			_aManagement and Labour Studies
300			_a49(4), Nov, 2024: p.679-703
520			_aUsing the Self-exciting Threshold Autoregressive Model (SETAR_M) and linear models such as the vector error correction model (VECM), and univariate models, this article specifies forecasting models for exchange rate volatilities in Ghana and compares their forecasts accuracy using Diebold–Mariano and Pesaran-Timmermann tests statistics. The relevance of this research is to equip business owners and businesses on managing forex losses and to reduce their impact on profits, productivity and employment in high volatile and unstable currency environments. The research concludes that the non-linear SETAR model is superior to the linear models in predicting short-term volatilities in exchange rates, while the fundamentally based linear model is superior for predicting long-term volatility in exchange rates. Therefore, short-term business commitments or transactions such as raw material purchases, cash expenses or incomes in foreign currencies should be planned or managed using SETAR or a non-linear model, whereas long-term contractual obligations like futures and forward contracts should be planned with a fundamentally based multivariate linear model.- Reproduced https://journals.sagepub.com/doi/full/10.1177/0258042X241233043
650			_aGhana, Exchange rate, ARIMA models, SETAR models,, VAR models, Forecasting accuracy. _949715
773			_aManagement and Labour Studies
942			_cAR